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tannnuu

AI Pokemon Arena MCP

by tannnuu

battle_simulation

Simulates a Pokemon battle between two named Pokemon, using AI analysis of stats, types, and abilities to determine an outcome narrative. Enter both Pokemon to compare matchups.

Instructions

Simulate a battle between two Pokemon using AI analysis of their stats, types, and abilities

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pokemon1YesFirst Pokemon name or Pokedex number
pokemon2YesSecond Pokemon name or Pokedex number

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.3/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden. It does disclose that results come from 'AI analysis,' hinting at a non-deterministic, generated outcome rather than a fixed computation, which is genuinely useful. However, it omits latency, cost, determinism, and whether a canonical winner or a narrative is produced.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single, front-loaded sentence with no filler. Every clause ('simulate a battle,' 'two Pokemon,' 'AI analysis') earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema and no annotations, so the description should ideally say what the agent gets back (a predicted winner, probabilities, a battle narrative). It also doesn't state whether the same inputs always yield the same result. Adequate to invoke, but incomplete for a simulation tool with no structured output contract.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and both parameters ('First Pokemon name or Pokedex number') are fully documented in the schema, so the description adds no parameter meaning. Per the baseline rule for high coverage, a 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('simulate a battle between two Pokemon') and adds the mechanism ('AI analysis of stats, types, abilities'). It is clear what the tool does, though it does not name or distinguish itself from siblings like analyze_pokemon, which could plausibly be confused with it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description never says when to use this tool versus the sibling data-fetch tools (get_pokemon_data, analyze_pokemon, search_pokemon). No prerequisites, no exclusions, no alternatives are named; usage must be inferred entirely from the verb.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.